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Population-genomic inference of the strength and timing of selection against gene flow

View ORCID ProfileSimon Aeschbacher, Jessica P. Selby, John H. Willis, Graham Coop
doi: https://doi.org/10.1101/072736
Simon Aeschbacher
1Department of Evolution and Ecology, University of California, Davis, CA 95616.
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Jessica P. Selby
2Department of Biology, Duke University, Durham, NC 27708
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John H. Willis
2Department of Biology, Duke University, Durham, NC 27708
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Graham Coop
1Department of Evolution and Ecology, University of California, Davis, CA 95616.
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Abstract

The interplay of divergent selection and gene flow is key to understanding how populations adapt to local environments and how new species form. Here, we use DNA polymorphism data and genome-wide variation in recombination rate to jointly infer the strength and timing of selection, as well as the baseline level of gene flow under various demographic scenarios. We model how divergent selection leads to a negative correlation between recombination rate and genetic differentation among populations. Our theory shows that the selection density, i.e. the selection coefficient per base pair, is a key parameter underlying this relationship. We then develop a procedure for parameter estimation and apply it to two datasets from Mimulus guttatus. First, we infer a strong signal of adaptive divergence in the face of gene flow between populations growing on and off phytotoxic serpentine soils. However, the genome-wide intensity of this selection is not exceptional compared to what M. guttatus populations may typically experience when adapting to local conditions. Second, we find that selection against genome-wide introgression from the selfing sister species M. nasutus has acted to maintain a barrier between these two species over the last 250 to 500 ky. Our study provides a theoretical framework for linking genome-wide patterns of divergence and recombination with the underlying evolutionary mechanisms that drive this differentiation.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted October 10, 2016.
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Population-genomic inference of the strength and timing of selection against gene flow
Simon Aeschbacher, Jessica P. Selby, John H. Willis, Graham Coop
bioRxiv 072736; doi: https://doi.org/10.1101/072736
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Population-genomic inference of the strength and timing of selection against gene flow
Simon Aeschbacher, Jessica P. Selby, John H. Willis, Graham Coop
bioRxiv 072736; doi: https://doi.org/10.1101/072736

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